USDT + USDC Dominance USDT + USDC Dominance: This refers to the combined market capitalization of Tether (USDT) and USD Coin (USDC) as a percentage of the total cryptocurrency market capitalization. It measures the proportion of the crypto market held by these stablecoins, which are pegged to the US dollar. High dominance indicates a "risk-off" sentiment, where investors hold stablecoins for safety during market uncertainty. A drop in dominance suggests capital is flowing into riskier assets like altcoins, often signaling a bullish market or the start of an "alt season.
Sentiment
Momentum Commitment Delta (MCD)Momentum Commitment Delta (M C D)
⸻
What it is
M C D fuses five micro-structure clues into one 0-to-1 score that says, “how hard are traders actually leaning on this move?”
1. Body-Delta Momentum – average net candle body direction.
2. Volume Commitment – up-volume ÷ down-volume over the same window.
3. Wick Compression – shrinking upper/lower wicks = clean conviction.
4. Candle Sequencing – rewards orderly, staircase-style body growth.
5. Pin Ratio – where the close pins inside each candle’s range.
The five factors are multiplied, then auto-normalized so extremes always land near 0 / 1 on any symbol or timeframe.
I recommend tweaking the settings to fit your edge, the pre-loaded settings may not be suitable for most traders. The MCD works on all timeframes as well :)
⸻
How to read basic signals
• Fresh cross above 0.70 → often the birth of a real breakout.
• Cluster of > 0.70 bars → “commitment lock,” pull-backs usually shallow.
• Price makes new high while M C D doesn’t → beware...
• Cross back below 0.30 after a run → momentum is out of fuel.
⸻
Because M C D is multiplicative, it’s hard to hit the extremes—so when the bars light lime green, the print is usually telling the truth.
I personally use the MCD to identify the peak of a high-conviction range, NOT a breakout. If a bar prints over 0.70 (green) and then a range forms off of the bar which exceeded 0.70, the breakout has a high chance to be explosive, regardless of what MCD reads at the breakout inflection point.
Play around with it, im sure there are plenty of other patterns.
Disclaimer: The Momentum Commitment Delta (MCD) indicator is provided strictly for educational and informational purposes. It does not constitute financial or investment advice, nor is it a recommendation to buy or sell any security. Trading involves substantial risk, and you should always perform your own due diligence and consult a qualified financial professional before making any trading decisions. Past performance is not indicative of future results.
Monday Swing Box# Monday Swing Box Indicator - Trading Applications
This "Monday Swing Box" indicator can be very useful in trading for several strategic reasons:
## 1. **"Monday Effect" Analysis**
* **Concept**: Mondays often have particular characteristics in the markets (opening gaps, weekend catch-up, different volumes)
* **Utility**: Allows visualization and quantification of these Monday-specific movements
* **Application**: Helps identify recurring patterns in your strategy
## 2. **Relative Volatility Measurement with ATR**
* **The ATR percentage tells you**:
* **< 50%**: Low volatility Monday (possible consolidation)
* **50-100%**: Normal volatility
* **> 100%**: Very volatile Monday (important event, potential breakout)
* **Advantage**: Contextualizes the movement relative to historical volatility
## 3. **Practical Trading Applications**
### **For Day Trading**:
* **Entry**: A Monday with >150% ATR may signal a strong movement to follow
* **Stop Loss**: Adjust stop sizes according to Monday's volatility
* **Targets**: Calibrate targets according to the movement's magnitude
### **For Swing Trading**:
* **Support/Resistance**: Monday's high/low often become key levels
* **Breakout**: Breaking above/below Monday's box may signal continuation
* **Retracement**: Return to Monday's box = support/resistance zone
### **For Risk Management**:
* **Sizing**: Adapt position sizes according to measured volatility
* **Timing**: Avoid trading abnormally volatile Mondays if you prefer stability
## 4. **Specific Possible Strategies**
### **"Monday Breakout"**:
* Wait for a break above/below Monday's box
* Enter in the direction of the breakout
* Stop at the other end of the box
### **"Monday Reversal"**:
* If Monday shows >200% ATR, look for a reversal
* The box becomes a resistance/support zone
### **"Monday Range"**:
* Trade bounces off the box limits
* Particularly effective if ATR % is normal (50-100%)
## 5. **Visualization Advantages**
* **Historical**: See past patterns across multiple Mondays
* **Comparison**: Compare current volatility to previous Mondays
* **Anticipation**: Prepare your strategy according to the type of Monday observed
## 6. **Limitations to Consider**
* Monday patterns can vary according to markets and periods
* Don't trade solely on this indicator, but use it as a complement
* Consider macroeconomic context and news
This indicator is therefore particularly useful for traders who want to exploit Monday's specificities and have an objective measure of this day's relative volatility compared to normal market conditions.
Advanced Risk Appetite Index ProThe Advanced Risk Appetite Index (RAI) represents a sophisticated institutional-grade measurement system for quantifying market risk sentiment through proprietary multi-factor fundamental analysis. This indicator synthesizes behavioral finance theory, market microstructure research, and macroeconomic indicators to provide real-time assessment of market participants' risk tolerance and investment appetite.
## Theoretical Foundation
### Academic Framework
The Risk Appetite Index is grounded in established financial theory, particularly the behavioral finance paradigm introduced by Kahneman and Tversky (1979) in their seminal work on prospect theory¹. The indicator incorporates insights from market microstructure theory (O'Hara, 1995)² and extends the risk-on/risk-off framework developed by Kumar and Lee (2006)³ through advanced statistical modeling techniques.
The theoretical foundation draws from multiple academic disciplines:
**Behavioral Finance**: The indicator recognizes that market participants exhibit systematic biases in risk perception, as documented by Shefrin and Statman (1985)⁴. These cognitive biases create measurable patterns in asset pricing and cross-asset relationships.
**Market Microstructure**: Following the work of Hasbrouck (1991)⁵, the model incorporates liquidity dynamics and market structure effects that influence risk sentiment transmission.
**Macroeconomic Theory**: The indicator integrates insights from monetary economics (Taylor, 1993)⁶ and international finance (Dornbusch, 1976)⁷ to capture policy impact on market sentiment.
### Methodological Approach
The Advanced Risk Appetite Index employs a proprietary multi-factor modeling approach that combines elements of:
1. **Advanced Factor Analysis**: Following established methodologies from Fama and French (1993)⁸, the system identifies fundamental factors that explain risk appetite variations.
2. **Regime-Adaptive Modeling**: Incorporating insights from Hamilton (1989)⁹ on regime-switching models to adapt to changing market conditions.
3. **Robust Statistical Framework**: Implementation of robust estimation methods (Huber, 1981)¹⁰ to ensure signal reliability and minimize noise impact.
## Technical Architecture
### Proprietary Multi-Factor Framework
The indicator processes information from multiple fundamental market dimensions through a sophisticated weighting and normalization system. The specific factor selection and weighting methodology represents proprietary intellectual property developed through extensive empirical research and optimization.
**Statistical Processing**: All inputs undergo robust statistical transformation using advanced normalization techniques based on Rousseeuw and Croux (1993)²⁰ to ensure consistent signal generation across different market environments.
**Dynamic Adaptation**: The system incorporates dynamic weighting adjustments based on market regime detection, drawing from the dynamic factor model literature (Stock and Watson, 2002)²¹.
**Quality Assurance**: Multi-layered quality assessment ensures signal reliability through proprietary filtering mechanisms that evaluate:
- Factor consensus requirements
- Signal persistence validation
- Data quality thresholds
- Regime-dependent adjustments
## Implementation and Usage
### Professional Visualization
The indicator provides institutional-grade visualization through:
**Multi-Theme Color Schemes**: Eight professional color themes optimized for different trading environments, following data visualization best practices (Tufte, 2001)²².
**Dynamic Background System**: Real-time visual feedback system that provides immediate market risk appetite assessment.
**Signal Quality Indicators**: Professional-grade visual representations of signal strength and reliability metrics.
### Analytics Dashboard
The comprehensive dashboard provides key institutional metrics including:
- Strategy position status and signal tracking
- Risk level assessment and market sentiment indicators
- Uncertainty measurements and volatility forecasting
- Trading signal quality and regime identification
- Performance analytics and model diagnostics
### Professional Alert System
Comprehensive alert framework covering:
- Entry and exit signal notifications
- Threshold breach warnings
- Market regime change alerts
- Signal quality degradation warnings
## Trading Applications
### Signal Generation Framework
The indicator generates professionally validated signals through proprietary algorithms:
**Long Entry Signals**: Generated when risk appetite conditions satisfy multiple proprietary criteria, indicating favorable risk asset exposure conditions.
**Position Management Signals**: Generated when risk appetite deteriorates below critical thresholds, suggesting defensive positioning requirements.
### Risk Management Integration
The indicator seamlessly integrates with institutional risk management frameworks through:
- Real-time regime identification and classification
- Advanced volatility forecasting capabilities
- Crisis detection and early warning systems
- Comprehensive uncertainty quantification
### Multi-Timeframe Applications
While optimized for daily analysis, the indicator supports various analytical timeframes for:
- Strategic asset allocation decisions
- Tactical portfolio rebalancing
- Risk management applications
## Empirical Validation
### Performance Characteristics
The indicator has undergone extensive empirical validation across multiple market environments, demonstrating:
- Consistent performance across different market regimes
- Robust signal generation during crisis periods
- Effective risk-adjusted return enhancement capabilities
### Statistical Validation
All model components and signal generation rules have been validated using:
- Comprehensive out-of-sample testing protocols
- Monte Carlo simulation analysis
- Cross-regime performance evaluation
- Statistical significance testing
## Model Specifications
### Market Applications and Target Instruments
**Primary Target Market**: The Advanced Risk Appetite Index is specifically optimized for S&P 500 Index (SPX) analysis, where it demonstrates peak performance characteristics. The model's proprietary factor weighting and signal generation algorithms have been calibrated primarily against SPX historical data, ensuring optimal sensitivity to US large-cap equity market dynamics.
**Secondary Market Applications**: While designed for SPX, the indicator demonstrates robust performance across other major equity indices, including:
- NASDAQ-100 (NDX) and related instruments
- Dow Jones Industrial Average (DJIA)
- Russell 2000 (RUT) for small-cap exposure
- International indices with sufficient liquidity and data availability
**Cross-Market Validation**: The model's fundamental approach to risk appetite measurement provides meaningful signals across different equity markets, though performance characteristics may vary based on market structure, liquidity, and regional economic factors.
### Data Requirements
The indicator requires access to institutional-grade market data across multiple asset classes and economic indicators. Specific data requirements and processing methodologies are proprietary.
### Computational Framework
The system utilizes advanced computational techniques including:
- Robust statistical estimation methods
- Dynamic factor modeling approaches
- Regime-switching algorithms
- Real-time signal processing capabilities
## Limitations and Risk Disclosure
### Model Limitations
**Data Dependency**: The indicator requires comprehensive market data and may experience performance variations during periods of limited data availability.
**Regime Sensitivity**: Performance characteristics may vary across different market regimes and structural breaks.
### Risk Warnings
**Past Performance Disclaimer**: Historical results do not guarantee future performance. All trading involves substantial risk of loss.
**Model Risk**: Quantitative models are subject to model risk and may fail to predict future market movements accurately.
**Market Risk**: The indicator does not eliminate market risk and must be used within comprehensive risk management frameworks.
## Professional Applications
### Target Users
The Advanced Risk Appetite Index is designed for:
- Institutional portfolio managers and investment professionals
- Risk management teams and quantitative analysts
- Professional traders and hedge fund managers
- Academic researchers and financial consultants
### Integration Capabilities
The indicator supports integration with:
- Portfolio optimization and management systems
- Risk management and monitoring platforms
- Automated trading and execution systems
- Research and analytics databases
## References
1. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291.
2. O'Hara, M. (1995). Market Microstructure Theory. Cambridge, MA: Blackwell Publishers.
3. Kumar, A., & Lee, C. M. (2006). Retail Investor Sentiment and Return Comovements. Journal of Finance, 61(5), 2451-2486.
4. Shefrin, H., & Statman, M. (1985). The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence. Journal of Finance, 40(3), 777-790.
5. Hasbrouck, J. (1991). Measuring the Information Content of Stock Trades. Journal of Finance, 46(1), 179-207.
6. Taylor, J. B. (1993). Discretion versus Policy Rules in Practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.
7. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy, 84(6), 1161-1176.
8. Fama, E. F., & French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics, 33(1), 3-56.
9. Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
10. Huber, P. J. (1981). Robust Statistics. New York: John Wiley & Sons.
11. Breeden, D. T. (1979). An Intertemporal Asset Pricing Model with Stochastic Consumption and Investment Opportunities. Journal of Financial Economics, 7(3), 265-296.
12. Mishkin, F. S. (1990). What Does the Term Structure Tell Us About Future Inflation? Journal of Monetary Economics, 25(1), 77-95.
13. Estrella, A., & Hardouvelis, G. A. (1991). The Term Structure as a Predictor of Real Economic Activity. Journal of Finance, 46(2), 555-576.
14. Collin-Dufresne, P., Goldstein, R. S., & Martin, J. S. (2001). The Determinants of Credit Spread Changes. Journal of Finance, 56(6), 2177-2207.
15. Carr, P., & Wu, L. (2009). Variance Risk Premiums. Review of Financial Studies, 22(3), 1311-1341.
16. Engel, C. (1996). The Forward Discount Anomaly and the Risk Premium: A Survey of Recent Evidence. Journal of Empirical Finance, 3(2), 123-192.
17. Ranaldo, A., & Söderlind, P. (2010). Safe Haven Currencies. Review of Finance, 14(3), 385-407.
18. Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
19. Pástor, L., & Stambaugh, R. F. (2003). Liquidity Risk and Expected Stock Returns. Journal of Political Economy, 111(3), 642-685.
20. Rousseeuw, P. J., & Croux, C. (1993). Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424), 1273-1283.
21. Stock, J. H., & Watson, M. W. (2002). Dynamic Factor Models. Oxford Handbook of Econometrics, 1, 35-59.
22. Tufte, E. R. (2001). The Visual Display of Quantitative Information (2nd ed.). Cheshire, CT: Graphics Press.
RSI(14) Custom by ChadRSI 14 : this indicator works in low time frame like 1h and 4h, for entry long position and short position. when the line touch 70 mean the price is overbought, when the line touch 50 it"s neutral, and when the line touch 30 mean price is oversold.
[Enhanced] L1 Banker Move🧠 L1 Banker Move
This is a multi-layered momentum signal tool designed to reveal institutional activity before major price moves. It combines deep liquidity detection, price pressure dynamics, and short-term investor alignment to deliver actionable signals with clarity and precision.
Key Features:
🔴 Institutional Signal
Detects potential Level 1 banker moves based on deep price compression and long-term sweep logic (Lowest Low 90 + smoothed momentum spikes).
🔵 Institutional Build Phase
Shows stealth accumulation/distribution zones using low volatility buildup and compression-based ratios over the past 30 bars.
🟢 Short-Term Investor Signal
Confirms price shifts with VWAP cross, SMA structure, and fast/slow EMA delta acceleration. Useful for timing precision entries after institutional setups.
💜 Combined Strength Histogram
A composite momentum bar that blends all three layers to visually rank the power of each setup.
🎯 Smart Highlighting & Alerts
Background turns red when an institutional signal appears without retail confirmation—flagging early entry traps or front-running zones. Includes alert conditions to notify you of optimal entry moments.
Customization:
Adjust the EMA delta sensitivity
Choose your preferred institutional timeframe (default: Daily)
[Enhanced] L1 Banker MoveThis is a multi-layered momentum signal tool designed to reveal institutional activity before major price moves. It combines deep liquidity detection, price pressure dynamics, and short-term investor alignment to deliver actionable signals with clarity and precision.
Key Features:
🔴 Institutional Signal
Detects potential Level 1 banker moves based on deep price compression and long-term sweep logic (Lowest Low 90 + smoothed momentum spikes).
🔵 Institutional Build Phase
Shows stealth accumulation/distribution zones using low volatility buildup and compression-based ratios over the past 30 bars.
🟢 Short-Term Investor Signal
Confirms price shifts with VWAP cross, SMA structure, and fast/slow EMA delta acceleration. Useful for timing precision entries after institutional setups.
💜 Combined Strength Histogram
A composite momentum bar that blends all three layers to visually rank the power of each setup.
🎯 Smart Highlighting & Alerts
Background turns red when an institutional signal appears without retail confirmation—flagging early entry traps or front-running zones. Includes alert conditions to notify you of optimal entry moments.
Customization:
Adjust the EMA delta sensitivity
Choose your preferred institutional timeframe (default: Daily)
Intradayscanner – Institutional Interest (vs. RSP)This indicator measures volatility-adjusted Relative Residual Strength (RRS) of any symbol versus RSP (the Invesco S&P 500® Equal Weight ETF) to surface potential institutional interest overlooked by cap-weighted benchmarks.
Equal-weighted benchmark: Uses RSP instead of SPY, so each S&P 500 component carries equal influence—highlighting broad institutional flows beyond the largest names.
ATR normalization: Computes a “Divergence Index” by dividing RSP’s price move by its ATR(14), then adjusts the symbol’s move by that index and rescales by its own ATR(14). This isolates true outperformance.
Residual focus: RRS represents the portion of a symbol’s move unexplained by broad-market action, making it easier to spot when institutions rotate into specific stocks.
Visualization: Plots RRS as green/red histogram bars and overlays a 14-period EMA for trend smoothing.
AmazingTrend - Long OnlyUnlock powerful trend-following logic with this dynamic and fully customizable Pine Script™ strategy, designed for traders who want precision entries, adaptive exits, and beautiful chart visuals.
✅ Key Features:
Long Bias by Default – Designed to ride bullish momentum with intelligent entries and flexible exits.
Optional Short Capability – While optimized for longs, the engine is also fully capable of short-side logic with minor adaptation.
Multiple Entry Modes – Choose between:
Classic – Reversals only
Aggressive – Early trend detection
Conservative – Confirmed trend continuation
Momentum – Powered by ATR and price bursts
Exit Customization – Includes:
Classic – Balanced logic
Quick – Tight risk control
Trailing – Dynamic stop tracking
Time-Based – Scheduled profit-taking
Visual Feedback – Multi-layered trend glow, buy/exit highlights, and a clean on-chart info panel.
Commission + Order Size Logic – Simulate realistic brokerage conditions with configurable cost and size inputs.
🔍 Chart Compatibility:
For the best performance, we recommend:
✅ Heikin Ashi and Renko charts for clarity and noise reduction.
✅ Use Regular Candlestick Charts only on higher timeframes (Daily and above) for clean signals.
❌ Avoid lower timeframes 1second to 5minute it is not built for this.
🧠 Smart Trend Detection:
The strategy detects directional bias using smoothed ATR-based stops and automatically shifts between bullish and bearish regimes. Entry and exit logic responds dynamically to market strength, giving you the edge in both volatile and trending environments.
🧪 Strategy Tested:
Built for 100% portfolio allocation per trade
Designed for realistic backtests with slippage and commission settings backtest results on our page is 0.25 % on buy and sell so total 0.50 %
Works across multiple markets: Crypto, Forex, Stocks. (futures coming later)
📈 Ideal For:
for shorters. investors, long traders, i do not recommend scalping ever but thats up to you.
Swing and momentum setups
Renko & Heikin Ashi fans
beware tradingview dont support alerts on Renko charts.
accurate backtest results that reflect reality if you use it exactly as displayed.
🎁 This Invite-Only script includes lifetime updates and is optimized for Pine Script v5. Contact the author to gain access. we will ofc develop this script feel free to use any version you prefer in the future.
MADA Trader Zones📊 Institutional Bias Indicator
This indicator is based on the analysis of institutional evaluations of individual trading days. By assessing trader behavior on a daily basis, an average is created that indicates when a market is considered cheap or expensive. Combined with current sentiment, this results in potential signals for entries or exits.
⚠️ Important Note:
This indicator does not work autonomously. Its signals must always be interpreted in the context of the overall market structure. That’s why it serves as a supportive tool within our MADA Mentoring Program, where we teach institutional knowledge and decision-making processes in depth.
Dynamic Spot vs Perps Premium (Area Plot)This is a script to give you an easy overall view on the spot perp premium which could indicate the momentum is drove by spot or perps
Signalgo XSignalgo X
Signalgo X is a sophisticated indicator crafted for traders who demand a disciplined, multi-layered approach to market analysis and trade management. This overview will help you understand its capabilities, logic, and how it can elevate your trading.
Core Concept
Signalgo X is built to:
Scan multiple timeframes simultaneously for price, volume, and volatility patterns.
Filter out unreliable signals during periods of market hype or manipulation.
Automate trade management with dynamic take-profit (TP), stop-loss (SL), and trailing logic.
Deliver actionable, visual signals and alerts for timely, confident decisions.
Inputs & Controls
Preset System Parameters:
News Sensitivity: Determines how responsive the indicator is to price moves.
Hype Filter Strength: Sets how aggressively the system avoids volatile, manipulated, or news-driven periods.
User-Configurable:
Show TP/SL Logic: Turn on/off the display of take-profit and stop-loss levels directly on your chart.
How Signalgo X Works
1. Multi-Timeframe Market Analysis
Signalgo X continuously monitors:
Closing price
Trading volume
Volatility (ATR)
across six distinct timeframes, from 1 hour to 3 months. This layered approach ensures that signals are validated by both short-term momentum and long-term trends.
2. Price, Volume, and Volatility Synthesis
Price Change: The system tracks percentage changes over each timeframe to gauge momentum.
Volume Ratio: By comparing current volume to a moving average, it detects unusual spikes that may signal institutional activity or manipulation.
Volatility: Measures the intensity of price movements relative to average ranges, helping to identify breakout or exhaustion scenarios.
3. Proprietary Anti-Hype Filter
A unique scoring mechanism evaluates:
Volume spikes without corresponding price action
Sudden jumps in volatility
Conflicting signals across timeframes
Social hype proxies (e.g., sharp moves on low volume)
If the market is deemed “hyped,” all trading signals are suppressed and a clear warning is shown, keeping you out of unpredictable conditions.
4. Signal Classification & Mapping
Significant Moves: Only price actions that exceed a sensitivity threshold and are confirmed by volume/volatility are considered.
Bullish/Bearish Signals: Generated for each timeframe.
Signal Strength: Categorized as regular, or strong based on multi-timeframe agreement.
Entry & Exit Strategy
Entry Logic
Long (Buy) Entry: Triggered when bullish signals are detected (of any strength) and no hype is present.
Short (Sell) Entry: Triggered when bearish signals are detected and no hype is present.
Exit & Trade Management
Stop Loss (SL): Placed at a calculated distance from entry, adapting to recent volatility.
Take Profits (TP1, TP2, TP3): Three profit targets, each at a greater reward multiple.
Trailing Stop: After the first take-profit is hit, the stop-loss moves to breakeven and a trailing stop is activated to protect further gains.
Event Tracking: The indicator visually marks when each TP or SL is hit, providing real-time feedback.
Chart Plots: All relevant SL, TP, and trailing stop levels are clearly marked for both long and short trades.
Labels: Entry, exit, and signal strength events are color-coded and visually prominent.
Alerts: Built-in alert conditions allow you to set up TradingView notifications for strong/regular buy/sell signals and hype warnings.
Trading Strategy Application
Multi-Timeframe Confirmation: Only strong signals confirmed by several timeframes are acted upon, reducing false positives.
Volume & Volatility Awareness: The indicator avoids low-quality, “fakeout” signals by requiring confirmation from both price and volume/volatility.
Hype Avoidance: Keeps you out of the market during news-driven or manipulated periods, helping to protect your capital.
Automated Discipline: The TP/SL logic enforces a rules-based exit strategy, helping you lock in profits and limit losses without emotional interference.
Who Should Use Signalgo X?
Signalgo X is ideal for traders who want:
Systematic, high-confidence signals
Automated and disciplined trade management
Protection against unpredictable market events
Clear, actionable visuals and alerts
AD Line of S&P SectorsAdvance-Decline Line of S&P 500 Sectors
This indicator tracks the breadth strength of the S&P 500 by combining an unweighted Advance-Decline (A/D) Line and a market-cap weighted A/D Histogram across all 11 major S&P sectors.
Key Features
Sector A/D Histogram: Measures sector breadth based on whether each sector advanced or declined, then weights it by its current estimated market cap share.
Unweighted A/D Line: Smooth average of sectors equally weighted, giving an alternative breadth view that’s less biased by large sectors.
Top Weighted Stocks Tracker: Tracks the daily percentage change of the top 10 highest-weighted S&P 500 stocks, scaled by their index weights, and overlays them as a background area plot.
Zero Crossovers: Histogram and line crossing zero can help highlight broadening strength or weakness.
Customizable Sector Weights: Sector weights can be adjusted in the settings. It is recommended to review and update these periodically to reflect changes in S&P sector allocations.
Repaint Option: Uses a user-selectable repaint mode for flexible bar update logic.
How to Use
Trend Confirmation: When the weighted histogram and unweighted line are above zero together, it indicates broad sector strength; below zero suggests broad weakness.
Neutral Zone: Values between +0.5 and -0.5 (or your custom thresholds) may imply a ranging market or slower movement.
Top Names Context: The top-weighted stocks area shows how much the index’s largest components are pulling the market up or down, relative to the broader sector breadth.
⚠️ Disclaimer
This script is for educational and informational purposes only and does not constitute financial advice. Always do your own research and consult with a qualified financial professional before making trading decisions. Use at your own risk.
Performance Table (Custom Indexes)📄 Detailed description of your code:
✅ What this script is:
This is a TradingView Pine Script v5 indicator called "Performance Table (Custom Indexes)". It creates a performance table overlay on the chart, summarizing the percentage returns of the current symbol and up to three customizable indexes over four different lookback periods:
1 day (1D),1 week (1W),1 month (1M),3 months (3M)
Note - It calculate return for trading's days not calendar days
🔧 What it is useful for:
📊 Visual performance comparison: It allows traders to quickly compare the recent performance of the asset on the chart to selected benchmark indexes (like Nifty 50, Midcap 50, Small cap 50).
🎯 Relative strength analysis: It helps identify if the current asset is outperforming or underperforming these benchmarks over multiple timeframes.
🖥️ Clean UI: The performance data is neatly displayed in a configurable table directly on the chart without clutter.
💡 Use case example:
A trader looking at an individual stock can immediately see how it performed compared to benchmark indexes over 1 day, 1 week, 1 month, and 3 months—all right on their TradingView chart.
Delta Spike Detector [GSK-VIZAG-AP-INDIA]📌 Delta Spike Detector – Volume Imbalance Ratio
By GSK-VIZAG-AP-INDIA
📘 Overview
This indicator highlights aggressive buying or selling activity by analyzing the imbalance between estimated Buy and Sell volume per candle. It flags moments when one side dominates the other significantly — defined by user-selectable volume ratio thresholds (10x, 15x, 20x, 25x).
📊 How It Works
Buy/Sell Volume Estimation
Approximates buyer and seller participation using candle structure:
Buy Volume = Proximity of close to low
Sell Volume = Proximity of close to high
Delta & Delta Ratio
Delta = Buy Volume − Sell Volume
Delta Ratio = Ratio of dominant volume side to the weaker side
When this ratio exceeds a threshold, it’s classified as a spike.
Spike Labels
Labels are plotted on the chart:
10x B, 15x B, 20x B, 25x B → Buy Spike Labels (below candles)
10x S, 15x S, 20x S, 25x S → Sell Spike Labels (above candles)
The color of each label reflects the spike strength.
⚙️ User Inputs
Enable/Disable Buy or Sell Spikes
Set custom delta ratio thresholds (default: 10x, 15x, 20x, 25x)
🎯 Use Cases
Spotting sudden aggressive activity (e.g. smart money moves, traps, breakouts)
Identifying short-term market exhaustion or momentum bursts
Complementing other trend or volume-based tools
⚠️ Important Notes
The script uses approximated Buy/Sell Volume based on price position, not actual order flow.
This is not a buy/sell signal generator. It should be used in context with other confirmation indicators or market structure.
✍️ Credits
Developed by GSK-VIZAG-AP-INDIA
For educational and research use only.
Jags Dynamic S/R with Breakout & Weakness SignalsThis script is designed to automatically identify and display significant support and resistance levels on your chart. It then goes a step further by actively monitoring for potential breakouts and signs of support weakness.
Core Functionality: Identifying Key Levels
At its heart, the script uses a pivot logic to find recent price highs and lows, which it then plots as horizontal lines representing potential resistance and support, respectively. You have full control over how these levels are identified:
Timeframe: You can choose to find these pivot points on the current chart's timeframe or a higher one (e.g., daily pivots on an hourly chart).
Lookback Period: You can define how many bars to the left and right of a pivot point the script should consider, allowing you to fine-tune the significance of the levels it identifies.
Line Management: To keep your chart clean, you can set the maximum number of support and resistance lines to display. The script also has a clever "merge" feature that combines new pivot levels with existing ones if they are very close together, preventing clutter.
Breakout Detection
A key feature of this indicator is its ability to signal when the price breaks through one of these identified support or resistance levels. You can enable or disable this feature and choose from several confirmation methods to suit your trading style:
Simple Price Action: A breakout is confirmed simply by the price closing above a resistance level or below a support level.
ATR (Average True Range): For a breakout to be valid, the price must close a certain distance (based on the ATR) beyond the level, filtering out minor fluctuations.
Volume: This option adds another layer of confirmation by requiring a significant increase in trading volume during the breakout, suggesting strong conviction behind the move.
Momentum: This method uses the RSI (Relative Strength Index) to confirm that the breakout is supported by strong underlying momentum.
Quantitative: A more advanced option that uses a combination of the Rate of Change (ROC) and a Volume-Weighted Moving Average (VWMA) to provide a robust, multi-faceted confirmation of the breakout.
When a confirmed breakout occurs, the script will:
Color the breakout bar green for a bullish breakout (upward) or red for a bearish breakout (downward).
Place an arrow below a bullish breakout or above a bearish breakout.
Trigger an alert to notify you of the event.
Support Weakness Detection
To provide an early warning of a potential breakdown, the script includes a unique "Support Weakness Detection" feature. When enabled, it looks for a specific confluence of bearish signals as the price approaches a support level:
The price is hovering just above a key support level.
The short-term trend has already turned bearish (based on a moving average).
Momentum is fading (indicated by a falling RSI).
If all these conditions are met, a blue down-arrow will appear above the price bar, signalling that the nearby support may not hold.
Multi SMA AnalyzerMulti SMA Analyzer with Custom SMA Table & Advanced Session Logic
A feature-rich SMA analysis suite for traders, offering up to 7 configurable SMAs, in-depth trend detection, real-time table, and true session-aware calculations.
Ideal for those who want to combine intraday, swing, and higher-timeframe trend analysis with maximum chart flexibility.
Key Features
📊 Multi-SMA Overlay
- 7 SMAs (default: 5, 20, 50, 100, 200, 21, 34)—individually configurable (period, source, color, line style)
- Show/hide each SMA, custom line style (solid, stepline, circles), and color logic
- Dynamic color: full opacity above SMA, reduced when below
⏰ Session-Aware SMAs
- Each SMA can be calculated using only user-defined session hours/days/timezone
- “Ignore extended hours” option for accurate intraday trend
📋 Smart Data Table
- Live SMA values, % distance from price, and directional arrows (↑/↓/→)
- Bull/Bear/Sideways trend classification
- Custom table position, size, colors, transparency
- Table can run on chart or custom (higher) timeframe for multi-TF analysis
🎯 Golden/Death Cross Detection
- Flexible crossover engine: select any two from (5, 10, 20, 50, 100, 200) for fast/slow SMA cross signals
- Plots icons (★ Golden, 💀 Death), optional crossover labels with custom size/colors
🏷️ SMA Labels
- Optional on-chart SMA period labels
- Custom placement (above/below/on line), size, color, offset
🚨 Signal & Trend Engine
- Bull/Bear/Sideways logic: price vs. multiple SMAs (not just one pair)
- Volume spike detection (2x 20-period SMA)
- Bullish engulfing candlestick detection
- All signals can use chart or custom table timeframe
🎨 Visual Customization
- Dynamic background color (Bull: green, Bear: red, Neutral: gray)
- Every visual aspect is customizable: label/table colors, transparency, size, position
🔔 Built-in Alerts
- Crossovers (SMA20/50, Golden/Death)
- Bull trend, volume spikes, engulfing pattern—all alert-ready
How It Works
- Session Filtering:
- SMAs can be set to count only bars from your chosen market session, for true intraday/trading-hour signals
Dynamic Table & Signals:
- Table and all signal logic run on your selected chart or custom timeframe
Flexible Crossover:
- Choose any pair (5, 10, 20, 50, 100, 200) for cross detection—SMA 10 is available for crossover even if not shown as an SMA line
Everything is modular:
- Toggle features, set visuals, and alerts to your workflow
🚨 How to Use Alerts
- All key signals (crossovers, trend shifts, volume spikes, engulfing patterns) are available as alert conditions.
To enable:
- Click the “Alerts” (clock) icon at the top of TradingView.
- Select your desired signal (e.g., “Golden Cross”) from the condition dropdown.
- Set your alert preferences and create the alert.
- Now, you’ll get notified automatically whenever a signal occurs!
Perfect For
- Multi-timeframe and swing traders seeking higher timeframe SMA confirmation
- Intraday traders who want to ignore pre/post-market data
- Anyone wanting a modern, powerful, fully customizable multi-SMA overlay
// P.S: Experiment with Golden Cross where Fast SMA is 5 and Slow SMA is 20.
// Set custom timeframe for 4 hr while monitoring your chart on 15 min time frame.
// Enable Background Color and Use Table Timeframe for Background.
// Uncheck Pine labels in Style tab.
Clean, open-source, and loaded with pro features—enjoy!
Like, share, and let me know if you'd like any new features added.
Floor and Roof Indicator with SignalsFloor and Roof Indicator with Trading Signals
A comprehensive support and resistance indicator that identifies premium and discount zones with automated signal generation.
Key Features:
Dynamic Support/Resistance Zones: Calculates floor (support) and roof (resistance) levels using price action and volatility
Premium/Discount Zone Identification: Highlights areas where price may find resistance or support
Customizable Signal Frequency: Control how often signals are displayed (every Nth occurrence)
Visual Signal Table: Optional table showing the last 5 long and short signal prices
Multiple Timeframe Compatibility: Works across all timeframes
Technical Details:
Uses ATR-based calculations for dynamic zone width adjustment
Combines Bollinger Bands with highest/lowest price analysis
Smoothing options for cleaner signal generation
Fully customizable colors and display options
How to Use:
Floor Zones (Blue): Potential support areas where long positions may be considered
Roof Zones (Pink): Potential resistance areas where short positions may be considered
Signal Crosses: Visual markers when price interacts with key levels
Signal Table: Track recent signal prices for analysis
Settings:
Length: Period for calculations (default: 200)
Smooth: Smoothing factor for cleaner signals
Zone Width: Adjust the thickness of support/resistance zones
Signal Frequency: Control signal display frequency
Visual Options: Customize colors and table position
Alerts Available:
Long signal alerts when price touches discount zones
Short signal alerts when price reaches premium zones
Educational Purpose: This indicator is designed to help traders identify potential support and resistance areas. Always combine with proper risk management and additional analysis.
This description focuses on the technical aspects and educational value while avoiding any language that could be interpreted as financial advice or guaranteed profits.
THE HISTORY By [VXN]
THE HISTORY By - Monthly Seasonal Analysis Indicator
Development Status: This indicator is currently in the development phase and is not yet finished. Features and functionality may change as development continues.
Overview:
This indicator provides comprehensive historical analysis of monthly price patterns, designed to help traders identify recurring seasonal behaviors and market tendencies for the current month across multiple years of data.
Key Features:
Historical Data Analysis:
- Analyzes up to 10 years of historical performance for the current month
- Calculates monthly returns, win rates, and statistical metrics
- Tracks maximum drawdowns and runups for risk assessment
- Requires daily timeframe for accurate monthly calculations
Pattern Recognition:
- Implements a three-period classification system that breaks each month into segments
- Uses visual indicators (🟢🔴🟡) to represent bullish, bearish, and neutral periods
- Helps identify recurring intra-month behavior patterns
Statistical Display:
- Presents historical data in an organized table format
- Shows year-by-year performance comparisons
- Calculates average returns, best/worst performance, and confidence levels
- Displays overall market bias (bullish/bearish tendency) for the current month
Dynamic Zone Overlays:
- Projects Fibonacci-based support/resistance levels based on historical volatility
- Adjusts zone positioning based on the month's historical bias
- Provides visual reference points for potential price targets or reversal areas
Practical Applications:
- Seasonal trading strategy development
- Risk management through historical context
- Understanding market cyclicality and recurring patterns
- Educational tool for studying price behavior over time
Note: This indicator is designed for analysis and education purposes, helping traders understand historical market patterns rather than providing direct trading signals. The data should be used in conjunction with other forms of analysis and proper risk management. As this is still under development, please expect updates and refinements to functionality.
xGhozt Wickless Candle Streak ProbabilityThe xGhozt Wickless Candle Streak Probability is a custom Pine Script indicator designed to identify and quantify the occurrence of consecutive "wickless" candles of the same trend (either bullish or bearish).
Key Features:
Wickless Candle Detection: It first identifies candles that lack an upper or lower wick (meaning their open/close is equal to their high/low, respectively).
Consecutive Streak Tracking: The indicator tracks how many wickless bullish candles occur in a row, and similarly for wickless bearish candles.
User-Defined Streak Length: You can specify a Streak Length in the indicator's settings. This defines how many consecutive wickless candles are needed to register a "streak."
Probability Calculation: For the chosen Streak Length, the indicator calculates the historical probability (as a percentage) of encountering such a streak for both bullish and bearish wickless candles. This is done by dividing the number of times a streak of that length has occurred by the total number of candles scanned.
On-Chart Display: The results, including the total wickless candles, total scanned candles, and the calculated streak probabilities, are displayed in a convenient table directly on your chart.
Purpose:
This indicator helps traders and analysts understand the historical likelihood of sustained, strong directional moves as indicated by consecutive wickless candles. By quantifying these probabilities, it can provide insights into potential continuation patterns or extreme market conditions, which might be useful for developing trading strategies or confirming market biases.
BANKNIFTY Contribution Table [GSK-VIZAG-AP-INDIA]1. Overview
This indicator provides a real-time visual contribution table of the 12 constituent stocks in the BANKNIFTY index. It displays key metrics for each stock that help traders quickly understand how each component is impacting the index at any given moment.
2. Purpose / Trading Use Case
The tool is designed for intraday and short-term traders who rely on index movement and its internal strength or weakness. By seeing which stocks are contributing positively or negatively, traders can:
Confirm trend strength or divergence within the index.
Identify whether a BANKNIFTY move is broad-based or driven by a few heavyweights.
Detect reversals when individual components decouple from index direction.
3. Key Features and Logic
Live LTP: Current price of each BANKNIFTY stock.
Price Change: Difference between current LTP and previous day’s close.
% Change: Percentage move from previous close.
Weight %: Static weight of each stock within the BANKNIFTY index (user-defined).
This estimates how much each stock contributes to the BANKNIFTY’s point change.
Sorted View: The stocks are sorted by their weight (descending), so high-impact movers are always at the top.
4. User Inputs / Settings
Table Position (tableLocationOpt):
Choose where the table appears on the chart:
top_left, top_right, bottom_left, or bottom_right.
This helps position the table away from your price action or indicators.
5. Visual and Plotting Elements
Table Layout: 6 columns
Stock | Contribution | Weight % | LTP | Change | % Change
Color Coding:
Green/red for positive/negative price changes and contributions.
Alternating background rows for better visibility.
BANKNIFTY row is highlighted separately at the top.
Text & Background Colors are chosen for both readability and direction indication.
6. Tips for Effective Use
Use this table on 1-minute or 5-minute intraday charts to see near real-time market structure.
Watch for:
A few heavyweight stocks pulling the index alone (can signal weak internal breadth).
Broad green/red across all rows (signals strong directional momentum).
Combine this with price action or volume-based strategies for confirmation.
Best used during market hours for live updates.
7. What Makes It Unique
Unlike other contribution tables that show only static data or require paid feeds, this script:
Updates in real time.
Uses dynamic calculated contributions.
Places BANKNIFTY at the top and presents the entire internal structure clearly.
Doesn’t repaint or rely on lagging indicators.
8. Alerts / Additional Features
No alerts are added in this version.
(Optional: Alerts can be added to notify when a certain stock contributes above/below a threshold.)
9. Technical Concepts Used
request.security() to pull both 1-minute and daily close data.
Conditional color formatting based on price change direction.
Dynamic table rendering using table.new() and table.cell().
Static weights assigned manually for BANKNIFTY stocks (can be updated if index weights change).
10. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice or a buy/sell recommendation.
Users should test and validate the tool on paper or demo accounts before applying it to live trading.
📌 Note: Due to internet connectivity, data delays, or broker feeds, real-time values (LTP, change, contribution, etc.) may slightly differ from other platforms or terminals. Use this indicator as a supportive visual tool, not a sole decision-maker.
Script Title: BANKNIFTY Contribution Table -
Author: GSK-VIZAG-AP-INDIA
Version: Final Public Release
Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
